Stop the war!Остановите войну!
for scientists:
default search action
Google
Google Scholar
Semantic Scholar
Internet Archive Scholar
CiteSeerX
ORCIDLester Mackey
Lester W. Mackey
Person information
- affiliation: Microsoft Research
- affiliation: Stanford University, Department of Statistics
Refine list
refinements active!
zoomed in on ?? of ?? records
view refined list in
export refined list as
showing all ?? records
Books and Theses
- 2012
[b1]Lester Mackey:
Matrix Factorization and Matrix Concentration. University of California, Berkeley, USA, 2012
Journal Articles
- 2023
- [j7]Myra Cheng
, Maria De-Arteaga, Lester Mackey, Adam Tauman Kalai:
Social norm bias: residual harms of fairness-aware algorithms. Data Min. Knowl. Discov. 37(5): 1858-1884 (2023) - [j6]Carl-Johann Simon-Gabriel, Alessandro Barp, Bernhard Schölkopf, Lester Mackey:
Metrizing Weak Convergence with Maximum Mean Discrepancies. J. Mach. Learn. Res. 24: 184:1-184:20 (2023) - 2017
- [j5]Jonathan H. Chen, Mary K. Goldstein, Steven M. Asch, Lester W. Mackey, Russ B. Altman:
Predicting inpatient clinical order patterns with probabilistic topic models vs conventional order sets. J. Am. Medical Informatics Assoc. 24(3): 472-480 (2017) - 2015
- [j4]Lester W. Mackey, Ameet Talwalkar, Michael I. Jordan:
Distributed matrix completion and robust factorization. J. Mach. Learn. Res. 16: 913-960 (2015) - [j3]Tamara Broderick, Lester W. Mackey, John W. Paisley, Michael I. Jordan:
Combinatorial Clustering and the Beta Negative Binomial Process. IEEE Trans. Pattern Anal. Mach. Intell. 37(2): 290-306 (2015) - 2014
- [j2]Neil Zhenqiang Gong, Ameet Talwalkar, Lester W. Mackey, Ling Huang, Eui Chul Richard Shin, Emil Stefanov, Elaine Shi, Dawn Song:
Joint Link Prediction and Attribute Inference Using a Social-Attribute Network. ACM Trans. Intell. Syst. Technol. 5(2): 27:1-27:20 (2014) - [j1]Rina Foygel, Lester W. Mackey:
Corrupted Sensing: Novel Guarantees for Separating Structured Signals. IEEE Trans. Inf. Theory 60(2): 1223-1247 (2014)
Conference and Workshop Papers
- 2024
- [c46]Ayush Agrawal, Mirac Suzgun, Lester Mackey, Adam Kalai:
Do Language Models Know When They're Hallucinating References? EACL (Findings) 2024: 912-928 - 2023
- [c45]Carles Domingo-Enrich, Raaz Dwivedi, Lester Mackey:
Compress Then Test: Powerful Kernel Testing in Near-linear Time. AISTATS 2023: 1174-1218 - [c44]Hammaad Adam, Fan Yin, Huibin Hu, Neil A. Tenenholtz, Lorin Crawford, Lester Mackey, Allison Koenecke:
Should I Stop or Should I Go: Early Stopping with Heterogeneous Populations. NeurIPS 2023 - [c43]Soukayna Mouatadid, Paulo Orenstein, Genevieve Flaspohler, Miruna Oprescu, Judah Cohen, Franklyn Wang, Sean Knight, Maria Geogdzhayeva, Sam Levang, Ernest Fraenkel, Lester Mackey:
SubseasonalClimateUSA: A Dataset for Subseasonal Forecasting and Benchmarking. NeurIPS 2023 - [c42]Louis Sharrock, Lester Mackey, Christopher Nemeth:
Learning Rate Free Bayesian Inference in Constrained Domains. NeurIPS 2023 - [c41]Jiaxin Shi, Lester Mackey:
A Finite-Particle Convergence Rate for Stein Variational Gradient Descent. NeurIPS 2023 - 2022
- [c40]Raaz Dwivedi, Lester Mackey:
Generalized Kernel Thinning. ICLR 2022 - [c39]Abhishek Shetty, Raaz Dwivedi, Lester Mackey:
Distribution Compression in Near-Linear Time. ICLR 2022 - [c38]Jiaxin Shi, Chang Liu, Lester Mackey:
Sampling with Mirrored Stein Operators. ICLR 2022 - [c37]Niloy Biswas, Lester Mackey, Xiao-Li Meng:
Scalable Spike-and-Slab. ICML 2022: 2021-2040 - [c36]Jiaxin Shi, Yuhao Zhou, Jessica Hwang, Michalis K. Titsias, Lester Mackey:
Gradient Estimation with Discrete Stein Operators. NeurIPS 2022 - 2021
- [c35]Raaz Dwivedi, Lester Mackey:
Kernel Thinning. COLT 2021: 1753 - [c34]Tri Dao, Govinda M. Kamath, Vasilis Syrgkanis, Lester Mackey:
Knowledge Distillation as Semiparametric Inference. ICLR 2021 - [c33]Mikhail Khodak, Neil A. Tenenholtz, Lester Mackey, Nicolò Fusi:
Initialization and Regularization of Factorized Neural Layers. ICLR 2021 - [c32]Genevieve Flaspohler, Francesco Orabona, Judah Cohen, Soukayna Mouatadid, Miruna Oprescu, Paulo Orenstein, Lester Mackey:
Online Learning with Optimism and Delay. ICML 2021: 3363-3373 - 2020
- [c31]Anant Raj, Cameron Musco, Lester Mackey:
Importance Sampling via Local Sensitivity. AISTATS 2020: 3099-3109 - [c30]Ashia C. Wilson, Maximilian Kasy, Lester Mackey:
Approximate Cross-validation: Guarantees for Model Assessment and Selection. AISTATS 2020: 4530-4540 - [c29]Nilesh Tripuraneni, Lester Mackey:
Single Point Transductive Prediction. ICML 2020: 9593-9602 - [c28]Pierre Bayle, Alexandre Bayle, Lucas Janson, Lester Mackey:
Cross-validation Confidence Intervals for Test Error. NeurIPS 2020 - [c27]Nishanth Dikkala, Greg Lewis, Lester Mackey, Vasilis Syrgkanis:
Minimax Estimation of Conditional Moment Models. NeurIPS 2020 - [c26]Jackson Gorham, Anant Raj, Lester Mackey:
Stochastic Stein Discrepancies. NeurIPS 2020 - 2019
- [c25]Wilson Ye Chen, Alessandro Barp, François-Xavier Briol, Jackson Gorham, Mark A. Girolami, Lester W. Mackey, Chris J. Oates:
Stein Point Markov Chain Monte Carlo. ICML 2019: 1011-1021 - [c24]Jessica Hwang, Paulo Orenstein, Judah Cohen, Karl Pfeiffer, Lester Mackey:
Improving Subseasonal Forecasting in the Western U.S. with Machine Learning. KDD 2019: 2325-2335 - [c23]Xuechen Li, Yi Wu, Lester Mackey:
Stochastic Runge-Kutta Accelerates Langevin Monte Carlo and Beyond. NeurIPS 2019: 7746-7758 - [c22]Alessandro Barp, François-Xavier Briol, Andrew B. Duncan, Mark A. Girolami, Lester W. Mackey:
Minimum Stein Discrepancy Estimators. NeurIPS 2019: 12964-12976 - [c21]Ashia C. Wilson, Lester Mackey, Andre Wibisono:
Accelerating Rescaled Gradient Descent: Fast Optimization of Smooth Functions. NeurIPS 2019: 13533-13543 - 2018
- [c20]Wilson Ye Chen, Lester W. Mackey, Jackson Gorham, François-Xavier Briol, Chris J. Oates:
Stein Points. ICML 2018: 843-852 - [c19]Yash Deshpande, Lester W. Mackey, Vasilis Syrgkanis, Matt Taddy:
Accurate Inference for Adaptive Linear Models. ICML 2018: 1202-1211 - [c18]Ilias Zadik, Lester W. Mackey, Vasilis Syrgkanis:
Orthogonal Machine Learning: Power and Limitations. ICML 2018: 5723-5731 - [c17]Jimmy Wu, Diondra Peck, Scott Hsieh, Vandana Dialani, Constance D. Lehman, Bolei Zhou, Vasilis Syrgkanis, Lester W. Mackey, Genevieve Patterson:
Expert identification of visual primitives used by CNNs during mammogram classification. Medical Imaging: Computer-Aided Diagnosis 2018: 105752T - [c16]Jonathan H. Huggins, Lester Mackey:
Random Feature Stein Discrepancies. NeurIPS 2018: 1903-1913 - [c15]Murat A. Erdogdu, Lester Mackey, Ohad Shamir:
Global Non-convex Optimization with Discretized Diffusions. NeurIPS 2018: 9694-9703 - 2017
- [c14]Jackson Gorham, Lester W. Mackey:
Measuring Sample Quality with Kernels. ICML 2017: 1292-1301 - [c13]Ioannis Mitliagkas, Lester W. Mackey:
Improving Gibbs Sampler Scan Quality with DoGS. ICML 2017: 2469-2477 - 2016
- [c12]Jonathan H. Chen, Mary K. Goldstein, Steven M. Asch, Lester W. Mackey, Russ B. Altman:
Automated Organization of Electronic Health Record Data by Probabilistic Topic Modeling to Inform Clinical Decision Making. CRI 2016 - 2015
- [c11]Jackson Gorham, Lester W. Mackey:
Measuring Sample Quality with Stein's Method. NIPS 2015: 226-234 - 2014
- [c10]Lester W. Mackey, Jordan Bryan, Man Yue Mo:
Weighted Classification Cascades for Optimizing Discovery Significance in the HiggsML Challenge. HEPML@NIPS 2014: 129-134 - 2013
- [c9]Ameet Talwalkar, Lester W. Mackey, Yadong Mu, Shih-Fu Chang, Michael I. Jordan:
Distributed Low-Rank Subspace Segmentation. ICCV 2013: 3543-3550 - 2011
- [c8]Min-Yu Huang, Lester W. Mackey, Soile V. E. Keränen, Gunther H. Weber, Michael I. Jordan, David W. Knowles, Mark D. Biggin, Bernd Hamann:
Visually Relating Gene Expression and in vivo DNA Binding Data. BIBM 2011: 586-589 - [c7]Lester W. Mackey, Ameet Talwalkar, Michael I. Jordan:
Divide-and-Conquer Matrix Factorization. NIPS 2011: 1134-1142 - 2010
- [c6]John C. Duchi, Lester W. Mackey, Michael I. Jordan:
On the Consistency of Ranking Algorithms. ICML 2010: 327-334 - [c5]Lester W. Mackey, David J. Weiss, Michael I. Jordan:
Mixed Membership Matrix Factorization. ICML 2010: 711-718 - 2008
- [c4]Lester W. Mackey:
Deflation Methods for Sparse PCA. NIPS 2008: 1017-1024 - 2007
- [c3]Frances Perry, Lester W. Mackey, George A. Reis, Jay Ligatti, David I. August, David Walker:
Fault-tolerant typed assembly language. PLDI 2007: 42-53 - 2006
- [c2]Jordan L. Boyd-Graber, Sonya S. Nikolova, Karyn Moffatt, Kenrick C. Kin, Joshua Y. Lee, Lester W. Mackey, Marilyn Tremaine, Maria M. Klawe:
Participatory design with proxies: developing a desktop-PDA system to support people with aphasia. CHI 2006: 151-160 - [c1]David Walker, Lester W. Mackey, Jay Ligatti, George A. Reis, David I. August:
Static typing for a faulty lambda calculus. ICFP 2006: 38-49
Reference Works
- 2014
- [r1]Lester W. Mackey, David J. Weiss, Michael I. Jordan:
Mixed Membership Matrix Factorization. Handbook of Mixed Membership Models and Their Applications 2014: 351-367
Informal and Other Publications
- 2023
- [i57]Carles Domingo-Enrich, Raaz Dwivedi, Lester Mackey:
Compress Then Test: Powerful Kernel Testing in Near-linear Time. CoRR abs/2301.05974 (2023) - [i56]Louis Sharrock, Lester Mackey, Christopher Nemeth:
Learning Rate Free Bayesian Inference in Constrained Domains. CoRR abs/2305.14943 (2023) - [i55]Ayush Agrawal, Lester Mackey, Adam Tauman Kalai:
Do Language Models Know When They're Hallucinating References? CoRR abs/2305.18248 (2023) - [i54]Hammaad Adam, Fan Yin, Mary Hu, Neil A. Tenenholtz, Lorin Crawford, Lester Mackey, Allison Koenecke:
Should I Stop or Should I Go: Early Stopping with Heterogeneous Populations. CoRR abs/2306.11839 (2023) - [i53]Lily Xu, Esther Rolf, Sara Beery, Joseph R. Bennett, Tanya Y. Berger-Wolf, Tanya Birch, Elizabeth Bondi-Kelly, Justin Brashares, Melissa S. Chapman, Anthony Corso, Andrew Davies, Nikhil Garg, Angela Gaylard, Robert Heilmayr, Hannah Kerner, Konstantin Klemmer, Vipin Kumar, Lester Mackey, Claire Monteleoni, Paul Moorcroft, Jonathan Palmer, Andrew Perrault, David Thau, Milind Tambe:
Reflections from the Workshop on AI-Assisted Decision Making for Conservation. CoRR abs/2307.08774 (2023) - [i52]Eric Zelikman, Eliana Lorch, Lester Mackey, Adam Tauman Kalai:
Self-Taught Optimizer (STOP): Recursively Self-Improving Code Generation. CoRR abs/2310.02304 (2023) - [i51]Konstantin Klemmer, Esther Rolf, Caleb Robinson, Lester Mackey, Marc Rußwurm:
SatCLIP: Global, General-Purpose Location Embeddings with Satellite Imagery. CoRR abs/2311.17179 (2023) - 2022
- [i50]Jiaxin Shi, Yuhao Zhou, Jessica Hwang, Michalis K. Titsias, Lester Mackey:
Gradient Estimation with Discrete Stein Operators. CoRR abs/2202.09497 (2022) - [i49]Niloy Biswas, Lester Mackey, Xiao-Li Meng:
Scalable Spike-and-Slab. CoRR abs/2204.01668 (2022) - [i48]Soukayna Mouatadid, Paulo Orenstein, Genevieve Flaspohler, Judah Cohen, Miruna Oprescu, Ernest Fraenkel, Lester Mackey:
Adaptive Bias Correction for Improved Subseasonal Forecasting. CoRR abs/2209.10666 (2022) - [i47]Alessandro Barp, Carl-Johann Simon-Gabriel, Mark Girolami, Lester Mackey:
Targeted Separation and Convergence with Kernel Discrepancies. CoRR abs/2209.12835 (2022) - [i46]David Alvarez-Melis, Nicolò Fusi, Lester Mackey, Tal Wagner:
Budget-Constrained Bounds for Mini-Batch Estimation of Optimal Transport. CoRR abs/2210.13630 (2022) - [i45]Heishiro Kanagawa, Arthur Gretton, Lester Mackey:
Controlling Moments with Kernel Stein Discrepancies. CoRR abs/2211.05408 (2022) - [i44]Jiaxin Shi, Lester Mackey:
A Finite-Particle Convergence Rate for Stein Variational Gradient Descent. CoRR abs/2211.09721 (2022) - 2021
- [i43]Tri Dao, Govinda M. Kamath, Vasilis Syrgkanis, Lester Mackey:
Knowledge Distillation as Semiparametric Inference. CoRR abs/2104.09732 (2021) - [i42]Mikhail Khodak, Neil A. Tenenholtz, Lester Mackey, Nicolò Fusi:
Initialization and Regularization of Factorized Neural Layers. CoRR abs/2105.01029 (2021) - [i41]Raaz Dwivedi, Lester Mackey:
Kernel Thinning. CoRR abs/2105.05842 (2021) - [i40]Genevieve Flaspohler, Francesco Orabona, Judah Cohen, Soukayna Mouatadid, Miruna Oprescu, Paulo Orenstein, Lester Mackey:
Online Learning with Optimism and Delay. CoRR abs/2106.06885 (2021) - [i39]Jiaxin Shi, Chang Liu, Lester Mackey:
Sampling with Mirrored Stein Operators. CoRR abs/2106.12506 (2021) - [i38]Koulik Khamaru, Yash Deshpande, Lester Mackey, Martin J. Wainwright:
Near-optimal inference in adaptive linear regression. CoRR abs/2107.02266 (2021) - [i37]Myra Cheng, Maria De-Arteaga, Lester Mackey, Adam Tauman Kalai:
Social Norm Bias: Residual Harms of Fairness-Aware Algorithms. CoRR abs/2108.11056 (2021) - [i36]Soukayna Mouatadid, Paulo Orenstein, Genevieve Flaspohler, Miruna Oprescu, Judah Cohen, Franklyn Wang, Sean Knight, Maria Geogdzhayeva, Sam Levang, Ernest Fraenkel, Lester Mackey:
Learned Benchmarks for Subseasonal Forecasting. CoRR abs/2109.10399 (2021) - [i35]Raaz Dwivedi, Lester Mackey:
Generalized Kernel Thinning. CoRR abs/2110.01593 (2021) - [i34]Abhishek Shetty, Raaz Dwivedi, Lester Mackey:
Distribution Compression in Near-linear Time. CoRR abs/2111.07941 (2021) - [i33]Niloy Biswas, Lester Mackey:
Bounding Wasserstein distance with couplings. CoRR abs/2112.03152 (2021) - 2020
- [i32]Ashia C. Wilson, Maximilian Kasy, Lester Mackey:
Approximate Cross-validation: Guarantees for Model Assessment and Selection. CoRR abs/2003.00617 (2020) - [i31]Diana Cai, Rishit Sheth, Lester Mackey, Nicoló Fusi:
Weighted Meta-Learning. CoRR abs/2003.09465 (2020) - [i30]Nishanth Dikkala, Greg Lewis, Lester Mackey, Vasilis Syrgkanis:
Minimax Estimation of Conditional Moment Models. CoRR abs/2006.07201 (2020) - [i29]Carl-Johann Simon-Gabriel, Alessandro Barp, Lester Mackey:
Metrizing Weak Convergence with Maximum Mean Discrepancies. CoRR abs/2006.09268 (2020) - [i28]Jackson Gorham, Anant Raj, Lester Mackey:
Stochastic Stein Discrepancies. CoRR abs/2007.02857 (2020) - [i27]Pierre Bayle, Alexandre Bayle, Lucas Janson, Lester Mackey:
Cross-validation Confidence Intervals for Test Error. CoRR abs/2007.12671 (2020) - [i26]Anant Raj, Cameron Musco, Lester Mackey, Nicoló Fusi:
Model-specific Data Subsampling with Influence Functions. CoRR abs/2010.10218 (2020) - 2019
- [i25]Xuechen Li, Denny Wu, Lester Mackey, Murat A. Erdogdu:
Stochastic Runge-Kutta Accelerates Langevin Monte Carlo and Beyond. CoRR abs/1906.07868 (2019) - [i24]Alessandro Barp, François-Xavier Briol, Andrew B. Duncan, Mark A. Girolami, Lester W. Mackey:
Minimum Stein Discrepancy Estimators. CoRR abs/1906.08283 (2019) - [i23]Heishiro Kanagawa, Wittawat Jitkrittum, Lester Mackey, Kenji Fukumizu, Arthur Gretton:
A Kernel Stein Test for Comparing Latent Variable Models. CoRR abs/1907.00586 (2019) - [i22]Nilesh Tripuraneni, Lester Mackey:
Debiasing Linear Prediction. CoRR abs/1908.02341 (2019) - [i21]Anant Raj, Cameron Musco, Lester Mackey:
Importance Sampling via Local Sensitivity. CoRR abs/1911.01575 (2019) - 2018
- [i20]Jimmy Wu, Diondra Peck, Scott Hsieh, Vandana Dialani, Constance D. Lehman, Bolei Zhou, Vasilis Syrgkanis, Lester W. Mackey, Genevieve Patterson:
Expert identification of visual primitives used by CNNs during mammogram classification. CoRR abs/1803.04858 (2018) - [i19]Wilson Ye Chen, Lester W. Mackey, Jackson Gorham, François-Xavier Briol, Chris J. Oates:
Stein Points. CoRR abs/1803.10161 (2018) - [i18]Jimmy Wu, Bolei Zhou, Diondra Peck, Scott Hsieh, Vandana Dialani, Lester W. Mackey, Genevieve Patterson:
DeepMiner: Discovering Interpretable Representations for Mammogram Classification and Explanation. CoRR abs/1805.12323 (2018) - [i17]Jonathan H. Huggins, Lester Mackey:
Random Feature Stein Discrepancies. CoRR abs/1806.07788 (2018) - [i16]Jessica Hwang, Paulo Orenstein, Karl Pfeiffer, Judah Cohen, Lester Mackey:
Improving Subseasonal Forecasting in the Western U.S. with Machine Learning. CoRR abs/1809.07394 (2018) - [i15]Murat A. Erdogdu, Lester Mackey, Ohad Shamir:
Global Non-convex Optimization with Discretized Diffusions. CoRR abs/1810.12361 (2018) - [i14]Ruishan Liu, Nicoló Fusi, Lester Mackey:
Model Compression with Generative Adversarial Networks. CoRR abs/1812.02271 (2018) - 2017
- [i13]Jackson Gorham, Lester W. Mackey:
Measuring Sample Quality with Kernels. CoRR abs/1703.01717 (2017) - [i12]Ioannis Mitliagkas, Lester W. Mackey:
Improving Gibbs Sampler Scan Quality with DoGS. CoRR abs/1707.05807 (2017) - [i11]Lester W. Mackey, Vasilis Syrgkanis, Ilias Zadik:
Orthogonal Machine Learning: Power and Limitations. CoRR abs/1711.00342 (2017) - [i10]Yash Deshpande, Lester W. Mackey, Vasilis Syrgkanis, Matt Taddy:
Accurate Inference for Adaptive Linear Models. CoRR abs/1712.06695 (2017) - 2016
- [i9]Jack Gorham, Andrew B. Duncan, Sebastian J. Vollmer, Lester W. Mackey:
Measuring Sample Quality with Diffusions. CoRR abs/1611.06972 (2016) - 2015
- [i8]Jackson Gorham, Lester W. Mackey:
Measuring Sample Quality with Stein's Method. CoRR abs/1506.03039 (2015) - 2014
- [i7]Lester W. Mackey, Jordan Bryan:
Weighted Classification Cascades for Optimizing Discovery Significance in the HiggsML Challenge. CoRR abs/1409.2655 (2014) - 2013
- [i6]Ameet Talwalkar, Lester W. Mackey, Yadong Mu, Shih-Fu Chang, Michael I. Jordan:
Divide-and-Conquer Subspace Segmentation. CoRR abs/1304.5583 (2013) - [i5]Rina Foygel, Lester W. Mackey:
Corrupted Sensing: Novel Guarantees for Separating Structured Signals. CoRR abs/1305.2524 (2013) - 2012
- [i4]John C. Duchi, Lester W. Mackey, Michael I. Jordan:
The Asymptotics of Ranking Algorithms. CoRR abs/1204.1688 (2012) - 2011
- [i3]Lester W. Mackey, Ameet Talwalkar, Michael I. Jordan:
Divide-and-Conquer Matrix Factorization. CoRR abs/1107.0789 (2011) - [i2]Neil Zhenqiang Gong, Ameet Talwalkar, Lester W. Mackey, Ling Huang, Eui Chul Richard Shin, Emil Stefanov, Elaine Shi, Dawn Song:
Predicting Links and Inferring Attributes using a Social-Attribute Network (SAN). CoRR abs/1112.3265 (2011) - 2009
- [i1]Joseph Sill, Gábor Takács, Lester W. Mackey, David Lin:
Feature-Weighted Linear Stacking. CoRR abs/0911.0460 (2009)
Coauthor Index
a service of 
manage site settings
To protect your privacy, all features that rely on external API calls from your browser are turned off by default. You need to opt-in for them to become active. All settings here will be stored as cookies with your web browser. For more information see our F.A.Q.
Unpaywalled article links
Add open access links from 
to the list of external document links (if available).
Privacy notice: By enabling the option above, your browser will contact the API of unpaywall.org to load hyperlinks to open access articles. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Unpaywall privacy policy.
Archived links via Wayback Machine
For web page which are no longer available, try to retrieve content from the 
of the Internet Archive (if available).
Privacy notice: By enabling the option above, your browser will contact the API of archive.org to check for archived content of web pages that are no longer available. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Internet Archive privacy policy.
Reference lists
Add a list of references from 
, 
, and 
to record detail pages.
load references from crossref.org and opencitations.net
Privacy notice: By enabling the option above, your browser will contact the APIs of crossref.org, opencitations.net, and semanticscholar.org to load article reference information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Crossref privacy policy and the OpenCitations privacy policy, as well as the AI2 Privacy Policy covering Semantic Scholar.
Citation data
Add a list of citing articles from and to record detail pages.
load citations from opencitations.net
Privacy notice: By enabling the option above, your browser will contact the API of opencitations.net and semanticscholar.org to load citation information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the OpenCitations privacy policy as well as the AI2 Privacy Policy covering Semantic Scholar.
OpenAlex data
Load additional information about publications from 
.
Privacy notice: By enabling the option above, your browser will contact the API of openalex.org to load additional information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the information given by OpenAlex.
last updated on 2024-04-25 02:43 CEST by the dblp team
all metadata released as open data under CC0 1.0 license
see also: Terms of Use | Privacy Policy | Imprint
dblp was originally created in 1993 at:
since 2018, dblp has been operated and maintained by:
the dblp computer science bibliography is funded and supported by:
